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\title{Job Creation in Energy: Wind versus
  Unconventional oil and gas}
\author{Peter Hartley \\Kenneth B. Medlock III \\Ted Temzelides\\
  Xinya. Zhang}
\institute{Department of Economics and\\James A. Baker III Institute for Public Policy,
  \\ Rice University}
\date{Brown Bag Seminar, Rice University \\ February 2013}

\begin{document}

\frame{\titlepage}

\frame{
  \frametitle{Introduction}
Motivation
  \begin{itemize}
  \item An extensive ongoing policy discussion on renewable energy 
  \item Job opportunities in the renewable energy sector are assumed to be long lasting
  \item Shale oil and gas revolution has been taken place at the same time 
  \end{itemize}
To Do
\begin{itemize}
  \item collect data on the historical job creation for each energy source 
  \item Estimate job-creating potential of wind industry versus shale oil\&gas industry 
  \end{itemize}
}
\frame
{
  \frametitle{Subsidy in energy sector}
    \begin{figure}[ht]
      \centering \includegraphics[width=4in]{subsidy.jpg}
    \end{figure}
}

\frame
{
  \frametitle{Installed Wind Capacity in U.S}
  \begin{columns}
    \column{0.6\textwidth}
    \begin{figure}[ht]
      \centering \includegraphics[width=4in]{windprod.jpg}
    \end{figure}
    \column{0.3\textwidth}
   %  \begin{scriptsize}
%      Wind energy accounted
% for about 75\% of newly installed U.S. renewable electricity capacity
% in 2011 while electricity generation from biomass, geothermal, and
% hydropower have remained relatively stable since 2000
%          \end{scriptsize}
  \end{columns}
}
\frame
{
  \frametitle{Shale Production in U.S}
  \begin{columns}
    \column{0.6\textwidth}
    \begin{figure}[ht]
      \centering \includegraphics[width=3in]{shaleprod.jpg}
    \end{figure}
    \column{0.3\textwidth}
\begin{scriptsize}
Shale oil and gas revolution has been taking place, and has led to economic revitalization and job creation in places like Texas, North Dakota, West Pennsylvania, Louisiana, etc
    \end{scriptsize}
  \end{columns}
}


% \frame{
%   \frametitle{Literature}
%   \begin{itemize}
%   \item Input/Output(I/O) Model: IMPLAN, JEDI
%   \item Survey from Employers  
%   \item ``Oil Boom in Eagle Ford Shale'' by Federal Reserve Bank of Dallas 
% \item 
%   \end{itemize}
% }

\frame{
  \frametitle{Data Description}
 Balanced panel with N = 254 county observations in Texas and T = 132 months in 11 years from 2001 to 2011
 \begin{itemize}  
 \item Rich shale oil/gas resources and wind resource
 \item National leader in wind installations and
   is a manufacturing hub for the wind energy industry
 \item Wind online capacity 12,218 MW in 2012, 20\% of total U.S. wind power capacity installations 60,007 MW
 \item In 2010, 2218 bcf dry shale gas, 40\% of total U.S. production 5336 bcf
 \end{itemize}
}

\frame{
  \frametitle{Data Description - Variables}
  For counties i = 1, ..., 254 and months t = 1, ..., 132, the variables are:
  \begin{itemize}
  \item Total employment in all industries: emp$_ {it}$
  \item Real weekly average wage (adjusted by GDP deflator from BEA): wage$_ {it}$
  \item \# wells completed(directional, fractured; by completion date): wells$_ {it}$
  \item Cumulative \# wells completed: cumuwells$_ {it}$
  \item New installed wind capacity added (in MW): newcap$_ {it}$
  \item Cumulative installed wind capacity (in MW): cumucap$_ {it}$
  \end{itemize}
}



\frame{
  \frametitle{Data Description - Employment \& Wage}
  \begin{itemize}
  \item Employment and wage data taken from Quarterly Census of
    Employment and Wages (QCEW) Database of the Bureau of Labor
    Statistics (BLS)
  \item Use data from all industries (as opposed to energy-specific ones)
  \item Capture indirect/induced job contribution to other industries in the local economy 
  \item Data for many industry sectors/sub-sectors
    not available at the county level
  \end{itemize}
}

\frame{
  \frametitle{Data Description - Shale Industry}
  \begin{itemize}
  \item Well completion dates and located counties: Drilling Info Database
  \item 31,050 wells completed in 174 counties during 2001 - 2011
  \item Using completion date because hydraulic fracturing is a completion process and most labor intensive 
  \end{itemize}
}

\frame{
\frametitle{Data Description - Wind Industry}
  \begin{itemize}
  \item Installed capacity and online date:
    {\it American Wind Energy Association} (AWEA)
  \item Located the corresponding county from each wind project’ websites 
  \item 125 wind projects, 10006 MW wind capacity, has installed in 41 counties during 2001 - 2011
  \end{itemize}
}



\frame{
  \frametitle{Regression Model}
  \begin{itemize}
  \item Impact on Employment 
 \begin{align*}
    \text{emp}_{it} &=\beta_{1}\text{wells}_{it} + \beta_{2}\text{cumuwells}_{it} + \beta_{3}\text{newcap}_{it} \\ &+ \beta_{4}\text{cumuCap}_{it} + \alpha_{emp,i} + \gamma_{emp,t} + \epsilon_{emp,it}
  \end{align*}
\item Impact on Wage
  \begin{align*}
    \text{wage}_{it} &=\omega_{1}\text{wells}_{it} + \omega_{2}\text{cumuwells}_{it} + \omega_{3}\text{newcap}_{it} \\ &+ \omega_{4}\text{cumuCap}_{it} + \alpha_{wage,i} + \gamma_{wage,t} + \epsilon_{wage,it}
  \end{align*}
\item $\alpha$: County specific effects\,\,\, $\gamma$: Time effects 
  \end{itemize}
}
\frame{
  \frametitle{Results}
  \begin{table}[h]
  \begin{center}
    \begin{tabular}{|l|c|c|c|c|}
      \hline
      & \multicolumn{2}{|c|}{emp} & \multicolumn{2}{|c|}{wage} \\
      \hline
      & Estimate & Std.Error & Estimate  & Std.Error \\
      \hline
       wells & 89.4269 *** & 15.01109 & 0.2543 * & 0.1021 \\
       \hline{}
      cumuwells & 6.40665 *** & 0.32080 & 0.0002 & 0.0022 \\
      \hline{}
      newcap & -1.34376 & 6.45753 & 0.0303 & 0.0439 \\    
      \hline
      cumucap &  -0.29436 &   0.68288 & 0.0389 *** & 0.0046 \\   
      \hline
      \multicolumn{5}{|l|}{Significant codes: $0$ `` *** " 0.001 `` ** " 0.01 `` * " 0.05 `` . " 1 ``   "} \\
      \hline
    \end{tabular}
    \caption{Panel data model with spacial specific effects and time effects}
    \label{nonSpacial}
  \end{center}
\end{table}
}

\frame{
  \frametitle{Results}
\begin{columns}
    \column{0.5\textwidth}
    \begin{scriptsize}
Impact on Employment
  \begin{itemize}
  \item 89 short term jobs can be created per well completion
  \item 6 long term jobs per each completed well
  \item Given that 5,482 new directional/fractured wells were completed in Texas in 2011, 73550 new full-time jobs were created 
  \item Wind impact on employment has not been detected 
  \end{itemize}
      \end{scriptsize}
    \column{0.5\textwidth}
    \begin{scriptsize}
Impact on Wage
\begin{itemize}
\item 1 MW additional wind capacity will increase long term weekly average wage by 4 cents but short term impact is statistically insignificant
\item 25 cents wage increase due to well drilling activity in short term
\item Shale wells have no impact to the long term county wage level
  \item Analysis does not take into account distortions from subsidies/taxes associated with wind
  \end{itemize}
    \end{scriptsize}  
\end{columns}

}
\frame{
\frametitle{Results from other literature} 
 \begin{itemize}
  \item Employment Impacts for Eagle Ford Shale
at the 14-County Regional Level (2011): 38001 full time jobs
  \item Gulf Wind Project: 283.2 MW, 250-300 jobs during peak construction period, 15 - 20 permanent jobs
   \end{itemize}
 }


\frame{
  \frametitle{Spatial Interaction Effects}
  \begin{itemize}
  \item Spatial interactions could be due to competition between counties, spill-overs, externalities, regional issues, etc
  \item 254*254 spatial weights matrix $W$:
    \begin{align*}
        w_{ij} = 
  \begin{cases}
    1, \text{ if $i$ and $j$ are neighbors}, i\neq j\\
    0, \text{ otherwise}
  \end{cases}
    \end{align*}
  \item Then transform $W$ into row-standardized form, which assumes 
the impact on each unit by all other units are equal
  \end{itemize}
}

\frame{
  \frametitle{}
\underline {Spatial lag model}
    \begin{align*}
      \text{emp}_{it} &= \lambda\sum_{j=1}^N w_{ij}\text{emp}_{jt} + \beta_{1}\text{wells}_{it} + \beta_{2}\text{cumuwells}_{it}\\ &+ \beta_{3}\text{newcap}_{it} + \beta_{4}\text{cumuCap}_{it} + \alpha_{i} + \gamma_{t} + \epsilon_{it} \\
\lambda\;&\text{: spatial autoregressive coefficient}
  \end{align*}
\underline{Spatial error model}
 
\begin{align*}
      \text{emp}_{it} &= \beta_{1}\text{wells}_{it} + \beta_{2}\text{cumuwells}_{it} + \beta_{3}\text{newcap}_{it} \\ &+ \beta_{4}\text{cumuCap}_{it} + u_{it} \\
      \text{where}\;&u_{it} = \rho\sum_{j=1}^N w_{ij}u_{jt}+\alpha_{i} + \gamma_{t} + \epsilon_{it} \\
\rho\;&\text{: spatial autocorrelation parameter}
    \end{align*}
}
\frame{
  \frametitle{}
  \begin{table}[h]
    \begin{center}
      \begin{tabular}{|l|c|c|c|c|}
        \hline
        & \multicolumn{2}{|c|}{emp} & \multicolumn{2}{|c|}{wage} \\
        \hline 
        & lag & err & lag & err \\
        \hline      
        $\lambda$ &  0.1676*** & $N/A$ & 0.2618***& $N/A$\\
        \hline
        $\rho$ & $N/A$ & 0.1763*** & $N/A$ & 0.2627*** \\
        \hline
        wells       & 86.3790*** &86.2683*** & 0.1936 . & 0.1512 \\
        \hline
        cumuwells   & 6.0973*** & 6,8716*** & -0.0004& -0.001\\
        \hline
        newcap      & -1.3059001 & -1.2010 &0.0323 & 0.0349\\
        \hline
        cumucap     & 0.2174379  &0.5630 &0.0390***& 0.0424***\\
        \hline
        \multicolumn{5}{|l|}{Significant codes: $0$ `` *** " 0.001 `` ** " 0.01 `` * " 0.05 `` . " 1 ``   "} \\
        \hline
      \end{tabular}
      \caption{ Spacial interaction  effects on employment and wage}
    \end{center}
  \end{table}
}

\frame{
  \frametitle{Spatial panel results}
  \begin{itemize}
  \item Both $\lambda$ and $\rho$ are statistically significant
  \item Both models achieve similar results
  \item Excluding the spacial interaction effects, the shale activity impact on employment decrease from 89 to 86  
  \item the shale activity impact on wage is smaller and no longer significant on 0.05 level, while the impact of wind activity on wage get strengthened somehow
  \end{itemize}
}

\frame{
  \frametitle{Future Work}
  \begin{itemize}
  \item Work on other regions to get national wide data
  \item Add solar industry into the comparison
  \item Study the impact of subsidy on employment and wage 
  \item Policy guide for local economy
  \end{itemize}
}



\end{document}
